Automated UAT for Regulated Payment Systems: Property-Based Testing, Synthetic Data Generation, and IFRS/GAAP Revenue-Recognition Validation Gates

Automated User Acceptance Testing (UAT) is becoming a cornerstone in regulated payment systems, where technical reliability and financial compliance must operate in unison. Traditional manual UAT approaches often fail to provide the scalability, accuracy, and coverage required to validate complex payment workflows under stringent accounting standards. This review explores how property-based testing and synthetic data generation can enhance automated UAT frameworks, offering systematic validation of transaction invariants, expanded scenario coverage, and improved data privacy protections. A central focus is the integration of International Financial Reporting Standards (IFRS 15) and Generally Accepted Accounting Principles (ASC 606) through revenue-recognition validation gates, which embed accounting compliance into testing pipelines. Case studies from banking, FinTech, and payment service providers illustrate how these methods strengthen auditability, reduce compliance risks, and support transparent financial reporting. Emerging trends—including the adoption of artificial intelligence, continuous testing in DevOps environments, and cloud-enabled platforms—are identified as shaping the future of automated UAT. The review concludes that bridging technical testing with financial governance not only ensures regulatory compliance but also enhances operational resilience, scalability, and trust in modern payment infrastructures.